Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add sequenzia/agent-alchemy/plugin install agent-alchemy-dev-toolsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/sequenzia/agent-alchemy/feature-dev)<a href="https://agentmods.dev/skills/sequenzia/agent-alchemy/feature-dev"><img src="https://agentmods.dev/badge/skills/sequenzia/agent-alchemy/feature-dev/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/sequenzia/agent-alchemy/feature-dev"><img src="https://agentmods.dev/badge/skills/sequenzia/agent-alchemy/feature-dev.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00026 | $0.02277 |
| Opus 5.5 | $0.00010 | $0.00911 |
| Sonnet 5.5 | $0.00005 | $0.00455 |
| Haiku 4.5 | $0.00003 | $0.00228 |
Grade A, and why
feature-dev scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 276 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Feature Development Workflow
Execute a structured 7-phase feature development workflow. This workflow guides you through understanding, exploring, designing, implementing, and reviewing a feature.
CRITICAL: Complete ALL 7 phases. The workflow is not complete until Phase 7: Summary is finished. After completing each phase, immediately proceed to the next phase without waiting for user prompts.
Phase Overview
Execute these phases in order, completing ALL of them:
- Discovery - Understand the feature requirements
- Codebase Exploration - Map relevant code areas
- Clarifying Questions - Resolve ambiguities
- Architecture Design - Design the implementation approach
- Implementation - Build the feature
- Quality Review - Review for issues
- Summary - Document accomplishments
Phase 1: Discovery
Goal: Understand what the user wants to build.
-
Analyze the feature description from
$ARGUMENTS:- What is the core functionality?
- What are the expected inputs and outputs?
- Are there any constraints mentioned?
- What success criteria can you infer?
-
Summarize your understanding to the user. Use AskUserQuestion to confirm if your understanding is correct before proceeding.
Phase 2: Codebase Exploration
Goal: Understand the relevant parts of the codebase.
-
Run deep-analysis workflow:
- Read
${CLAUDE_PLUGIN_ROOT}/../core-tools/skills/deep-analysis/SKILL.mdand follow its workflow - Pass the feature description from Phase 1 as the analysis context
- This handles reconnaissance, team planning, approval (auto-approved when skill-invoked), team creation, parallel exploration (code-explorer agents), and synthesis (code-synthesizer agent)
- Note: Deep-analysis may return cached results if a valid exploration cache exists. In skill-invoked mode, cache hits are auto-accepted — this is expected behavior that avoids redundant exploration.
- Read
-
Present the synthesized analysis to the user.
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 276 lines · 26 tokens per session scan A 4b60f2300570
feature-dev is a skill published in the GitHub repository sequenzia/agent-alchemy (45 stars, last pushed 4mo ago), licensed MIT. It adds 26 tokens to every session and 2,277 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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a11y-audit
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